Besides the hyperparameters and setup we proposed in Section REF  on the synthetic dataset, we report the hyperparameters used for the results on the MNIST and CIFAR10. As stated in Section REF , we used that exact same experiment setup (network architectures, error thresholds, etc.) as in [1]} for fair and consistent comparisons. We used SGD optimizers, a learning rate of \(0.001\) , and a momentum of \(0.9\)  for traning on both datasets. For  MNIST, the training batch size was 1000. For  CIFAR10, the training batch size was 128. All pruning methods were performed 10 times, and we report the means and standard deviations in Figure REF  (with reweighting) and Figure REF  (without reweighting).
